Hospital admissions: An examination of race and health insurance

Size: px
Start display at page:

Download "Hospital admissions: An examination of race and health insurance"

Transcription

1 Volume: 5 Issue: 1 Year: 2008 Hospital admissions: An examination of race and health insurance Eric Gass, PhD Abstract This study examined the effects of racial differences and differences in insurance status on source of hospital admissions. The data source was the 2001 National Hospital Discharge Survey and included a sub-sample of 104,185 patients. 58.3% of patients were admitted through the emergency room, 75.0% of patients were White, 19.7% were Black, and 61.5% were on government insurance or uninsured. Black patients were found to have significantly higher levels of emergency room admissions (69.1%=p <.0001), regardless of insurance status (gov t/self-pay, 73.7%=p <.0001, private insurance, 59.5%=p <.0001). Patients on government insurance or self-payment had significantly higher levels of emergency room admissions (65.8%=p <.0001). Regression analysis showed that both race and insurance type are significant predictors (p <.0001) of Source of Admission to the hospital. Percent probabilities confirmed this finding. Thus, it was concluded that racial differences witnessed in source of admission were not mediated by insurance type and that race and insurance type are significant, independent predictors of hospital admission source. Keywords: Race, Ethnicity * Assistant Professor of Family and Community Medicine, Medical College of Wisconsin, Milwaukee, WI,

2 2 Introduction The term access to healthcare is discussed quite often in American society. However, defining access can be challenging. Berk and Schur (1998) performed a meta-analysis of access to healthcare studies performed in the 1980s and 1990s and concluded that at any one point in time between 11%-55% of Americans have difficulty accessing healthcare. Furthermore, those who are uninsured are between two and a half to eight times as likely to have difficulty accessing care compared to those who have health insurance (Berk and Schur, 1998). These findings have a wide range and may overestimate or underestimate access to care. Access can mean treatment at a free clinic, emergency room treatment, health insurance, having a consistent primary care physician, HMO rules and regulations, or hospital admission. The level of access being investigated will determine how many people can or do utilize a particular healthcare service. For example, theoretically, every member of society would have access to a free clinic. The quality of care may not be as good as that provided by a fee-charging or HMO provider, but medical care is provided nonetheless. If access to primary care is defined as having private health insurance that provides quality, primary care services, the numbers who do not have access would be quite large, compared to those who have access to free clinics. Keeping in mind these broad definitions of access, this study attempts to address the factors that predict access to hospital care. Specifically, what factors predict hospital admission through either physician referral or the emergency room? There is documented evidence that poor populations have higher incidences of chronic disease. Billings et al. (1993) examined this link and looked at the treatment options available to poor patients in New York City. In terms of hospital admissions, patients living in zip codes with an average income below $15,000 were 6.4 times more likely to be admitted to the hospital for asthma, than patients from zip codes with higher incomes. Similar results were found for diabetic coma (6.3 times greater), bacterial pneumonia (5.3 times greater), and congestive heart failure (4.6 times greater) (Billings et al., 1993). It was also found that Black low-income zip

3 3 codes had the greatest health disparities as compared to areas with higher incomes and that the greatest disparities occurred between young to middle age patients. Poor patients between the ages of had the greatest differences for number of hospital admissions, compared sameage middle class patients. These differences, although present, were not as strong for pediatric patients or elderly patients (Billings et al., 1993). Thus, people who should be at their healthiest, in young to middle adulthood, are most at risk for chronic health problems and hospitalization due to the effects of poverty. The trend of financially disadvantaged having greater levels of disease are seen elsewhere in the literature. Olowokure, Hawker, Weinberg, Gill, and Sufi (1999) found that, when breaking income down into quintiles, hospital admission for infectious intestinal diseases increase as income decreases. The rate of hospitalization for infectious intestinal diseases holds constant for the highest three income levels, but increases from 50 people hospitalized per 100,000 in the middle quintile to 100 people hospitalized per 100,000 for the last, and most destitute quintile. Many poor patients, like those described above, often seek non-emergency care at the emergency room. Kellerman (1991) summarized the factors that play into why patients choose the emergency room as a primary care source. Emergency departments are open 24 hours. If a person cannot afford to miss work to go to the doctor, or has childcare responsibilities during the day, the emergency room is a place to go in the evenings or overnight. Appointments, referrals, and immediate co-payments are not required for emergency care, thus an individual will not need to plan ahead or have to pay any money up front to see a physician, regardless of insurance status. Finally, other services are readily available in the emergency department environment, such as immediate, on-cite prescription filling and social workers, who can help the poor and often undereducated patient.

4 4 Primary care treatment has been shown to reduce emergency room use and hospital admissions for chronic diseases. In a study of patients with asthma or other chronic obstructive pulmonary diseases, the effects of non-emergency office visits are striking (Sin, Bell, Svenson, and Man, 2002). All patients had been recently been treated for their respiratory disease in the emergency room. Patients showed a 27% reduction in emergency room use over the next three months when an office visit occurred within one month of the initial emergency room visit that did not result in hospitalization (Sin et al., 2002). An 18% reduction in emergency room use over the next three months was found when an office visit occurred within one month of the initial emergency room visit that did result in hospitalization (Sin et al., 2002). Factors that resulted in a second emergency room visit within three months included older age and lowincome (Sin et al., 2002). These results clearly show significant reductions in emergency room treatment and hospitalization when chronic disease management occurs in the primary care setting. Many of these diseases could be preventable or treatable with access to primary care, yet uninsured patients or patients with Medicare or Medicaid have a more difficult time accessing healthcare. For example, Iserson and Kastre (1996) investigated if severity of illness presented by an uninsured patient affected medical treatment. In this case, 54 Arizona emergency rooms were contacted by woman posing as an uninsured patient with a minor rash, moderately sprained wrist, or severely debilitating headache. Race of the caller was not disclosed. No emergency room refused to see the uninsured patient, with 80% requesting that the patient come in immediately for treatment of the headache, 76% for the wrist injury, and 58% for the rash (Iserson and Kastre, 1996). When emergency treatment was not recommended, emergency room staff either recommended visiting a walk-in clinic or home remedies to relieve the discomfort. But, across all scenarios, emergency treatment was offered, even if not recommended by staff (Iserson and Kastre, 1996).

5 5 For comparison, the same woman called 69 private, primary care providers in the same cities as the previously contacted emergency departments. In this scenario however, the woman presented only a minor rash, since the practitioners might not be able to treat the other more severe ailments in their respective clinics (Iserson and Kastre, 1996). Also, the woman called each primary care practitioner twice, once as an uninsured patient, and once as a fully insured patient. In terms of seeing the uninsured patient, 62% of primary care physicians told the caller were not taking new patients or they would need at least $30 up front before seeing the patient. When these same physicians were called by an insured woman presenting a rash, 55% said they would see the woman for less than $30, and that only 40% were not taking new patients (Iserson and Kastre, 1996). Private physicians also offered less advice in terms of home treatment or referrals as opposed to emergency rooms. Thus, we can conclude from these results that private primary care physicians may not be open to any patient who is not fully covered by insurance. Disadvantages due to insurance status are also found for serious conditions, such as chronic heart problems. In a sample of patients admitted to the hospital after a heart attack, 52% of admissions were deemed to be low-risk (Butler, Hamumanthu, Chomsky, and Wilson, 1998). Low risk patients were defined as being in relatively good health, without life-threatening complications, with cardiac symptoms that could have been managed in a sub-acute setting. It was not reported on what proportion of patients were on Medicare, however, Medicare guidelines state that a patient cannot gain access to a sub-acute facility without spending at least three days in an acute care hospital in the previous month (Butler et al., 1998). If a patient were low-risk, in relatively good health and without complications, the chances of being hospitalized in an acute care facility would be relatively low. Thus, for low-risk patients on Medicare, hospitalization in an acute care facility is the only option for a condition that could be managed at outside the hospital, with a primary care physician, home health nurse and medication adjustment (Butler et al., 1998).

6 6 The literature also shows that there are racial differences in terms of accessing healthcare. For example, in a study of children with the common cold whose parents brought them to the emergency room, 91% of patients were Black (Mayefsky, El-Shinaway, & Kelleher, 1991). The common cold is not an emergent enough disease to seek treatment at an emergency room. Yet, this may be the only source of care available to minority patients. Black and Hispanic patients also show longer delays in seeking treatment for acute conditions such as heart attacks. In one particular study, minority patients had an average delay of over six hours before seeking treatment for a heart attack (Goldberg, Gurwitz, and Gore, 1999). As mentioned previously, it is possible that half of all heart attacks could be treated, or prevented, in a sub-acute setting (Butler et al., 1998). Thus, by delaying treatment, the risk of emergency treatment increases and longer hospitalization may result. To go back to a study mentioned previously, Billings et al. (1993), found that Black, lowincome zip codes had the greatest health disparities and hospitalizations for chronic conditions, as compared to areas with higher incomes. The Billings study is important, in a number of ways. It provides evidence that poverty is a condition for disease. It is common knowledge that longterm exposure to environmental toxins, such as mercury or asbestos, can lead to cancer or other illnesses. In the case of Billings et al. (1993), we could classify poverty as an environmental toxin, leading to increased levels of chronic conditions and hospitalizations among poor patients and Black patients. Coupled with the findings discussed previously, that minority patients and poor patients with insurance problems have greater difficulty accessing healthcare, a vicious cycle develops. In order to manage a chronic condition, primary care must be available. If primary care is not available and the chronic condition is not managed properly, the emergency room is utilized to provide relief from the chronic condition. However, at some point, improper management of the chronic condition will lead to hospitalization, either through a referral from a physician or through an emergency room, regardless of whether the emergency

7 7 room is being utilized for a true emergency or for a non-emergent need. What is unclear is what specific factor predicts hospital admission, race or insurance status. An attempt to resolve this dilemma will be addressed in this examination of hospital admission data. Methods The literature provides evidence that there are racial differences in access to healthcare, with minority patients having less access, especially to primary care. However, insurance status may be the influence underlying this difference. Thus, to test the hypothesis that racial differences in access to healthcare, as measured by source of hospital admission, will be mediated by differences in health insurance status, data from the 2001 National Hospital Discharge Survey (NHDS) will be analyzed. The NHDS has been collected every year since 1964 by the United States Department of Health and Human Services, National Center for Health Statistics. It is a national sample of all short-stay, non-federal hospitals. Thus, all Federal, military, and Veterans Administration hospitals were excluded from the sample. To be eligible, a hospital is defined as a facility having at least six staffed beds. All hospitals in the United States that have 1000 or more staffed beds are included every year. The remaining hospitals have a 1 in 40 chance of being selected in any given year. The sample used in this study originally consisted of 504 hospitals. Of these facilities, 27 were eliminated because they did not fit the criteria mentioned above (bed size, etc.) or were no longer operating. An additional 29 hospitals chose not to participate in the survey, brining the total number of facilities to 448. The data from the hospitals was complied through the use of medical records. Hospitals had the option of either manual or automated coding. A total of 41% of hospitals used the electronic coding system. For this method, the National Center for Health Statistics purchased the records from the hospitals themselves or from a state data tracking system. The remaining hospitals that used the manual system had the option to outsource their data

8 8 management to the United States Census Bureau for processing, or use their own medical records staff. Of the manual coding group, 28% of hospitals used their own medical records staff. The final patient population collected through these methods included 330,210 individuals, of which 36,410 were newborns. For the purposes of this analysis, all newborns (n=36,410) and patients 18 years of age or younger (n=31,444) were eliminated from the sample to ensure that subjects in the analysis had the potential to be covered by their own health insurance, and not that of their parents or guardians. The variables of interest in this study include source of hospital admission, race, and type of health insurance. For the dependent variable, source of hospital admission, 10 different categories were available for coding. These included: Physician referral, clinical referral, HMO referral, transfer from a hospital, transfer from a skilled nursing facility, transfer from other health facility, emergency room, court/law enforcement, other, or not available. Since there is no possibility of knowing the initial point of entry of patients who have already been admitted to the hospital and transferred to a facility participating in the study, these patients were eliminated from the data set. Also eliminated were those who entered the hospital through law enforcement or through other undocumented methods (n=93,285). For the independent variable, race of patient, eight different categories were available for coding: White, Black, American Indian/Alaska Native, Asian, Native Hawaiian or other Pacific Islander, Other, Multiple race stated, or not stated. For this analysis, those patients for which no race was stated were eliminated from the data set (n=61,468). Also, no measure of Latino ethnicity was provided in the data set, since Latinos are not considered a racial category. Finally, for the other independent variable, type of health insurance, 11 different categories were available for coding: Workers compensation, Medicare, Medicaid, other government payments, Blue Cross/Blue Shield, HMO/PPO, other private or commercial insurance, self pay, no charge, other, or not stated. For this analysis, those patients for which no insurance status was stated were eliminated

9 9 from the data set (n=3,418). This brings the final sample size to be used in this analysis to n=104,185. Results For the purposes of this analysis, variables were recoded into dichotomous groups or, in the case of Race, three groups. For the dependent variable, Source of Admission, physician referral, clinical referral, and HMO referral were grouped together into a new group called referral. The frequencies are reported in Table 1. Table 1 Percent Distribution of Source of Hospital Admission Source of Admission n % Emergency Room 60, % Referral 43, % Total 104, % For the independent variable of Race, American Indian/Alaska Native, Asian, Native Hawaiian or other Pacific Islander, and Other were recoded into a new group called Other, since no one racial group comprised more than 3.5% of the total sample. The frequencies are reported in Table 2. Table 2 Percent Distribution of Race Race n % White 78, % Black 20, % Other 5, % Total 104, % For the other independent variable of Insurance Type, the coverage types were reduced into two categories: Government/Self-Pay and Private Insurance. The types of coverage included in the Government/Self-Pay category include: Medicare, Medicaid, other government payments, self-pay, no charge, and other. The types of coverage included in the Private

10 10 Insurance include: Workers compensation, Blue Cross/Blue Shield, HMO/PPO, and other private or commercial insurance. The results are shown in Table 3. Table 3 Percent Distribution of Patients by Insurance Type Type of insurance coverage n % Government/Self-Pay 64, % Private Insurance 40, % Total 104, % Bivariate chi-square analyses were conducted to look at differences between groups within both independent variables in relation to the dependent variable, source of hospital admission. As can be seen in Table 4, a chi-square test found a significant association between race and source of admission to the hospital (p <.0001). To determine what differences existed between racial groups, a one-way analysis of variance (ANOVA) with a Bonferroni post-hoc analysis was performed. The results show no significant difference between White patients and patients of Other races (p <.463). However, significant differences were found between both White and Black patients (p <.0001) and between Black and patients from Other racial groups (p <.0001). Therefore, we can conclude that Black patients have significantly more hospital admissions through the emergency room than both White patients and patients of Other races. Table 4 Percent Distribution of Hospital Admission Source by Race Admission Source Race White (n=78,183) Black (n=20,505) Other (n=5497) Emergency Room 55.8% 69.1% 56.6% Physician Referral 44.4% 30.9% 43.4% Total 100% 100% 100% Chi-square value = df = 2, p <.0001

11 11 Again, using a chi-square test, Table 5 shows significant difference was found between type of insurance and source of admission to the hospital. Those on government insurance or paying on their own (65.8%) are significantly more likely to enter the hospital through the emergency room than through referral from a physician (46.5%) (p <.0001). Table 5 Percent Distribution of Hospital Admission by Insurance Type Admission Source Type of Insurance Govt./Self-Pay (n=64,114) Private Insurance (n=40,161) Emergency Room 65.8% 46.5% Physician Referral 34.2% 53.5% Total 100% 100% Chi-square value = df = 2, p <.0001 The analyses in Table 6 show an interesting result. Using chi-square analysis, there is a consistent significant association between Race and Source of Admission. Regardless of insurance status, racial differences exist for both patients on Government Insurance or Self-Pay (chi-square value = df = 2, p <.0001) and patients with Private Insurance (chi-square value = df = 2, p <.0001). To determine what differences existed between racial groups, a one-way analysis of variance (ANOVA) with a Bonferroni post-hoc analysis was performed for patients on government insurance or self-payment. The results show no

12 Table 6 Percent Distribution of Race by Source of Hospital Admission, Controlling for Insurance Type Type of Insurance Govt./Self-Pay* Private Insurance** Race White (n=46,799) Black (n=13,839) Other (n=3,476) White (n=31,384) Black (n=6,666) Other (n=2,021) Source of Admission Emergency Room Physician Referral 63.5% 73.7% 65.0% 44.0% 59.5% 42.3% 36.5% 26.3% 35.0% 56.0% 40.5% 57.7% Total 100% 100% 100% 100% 100% 100% * Chi-square value = df = 2, p <.0001 ** Chi-square value = df = 2, p <.0001 significant difference between White patients and patients of Other races (p <.214). However, significant differences were found between both White and Black patients (p <.0001) and between Black and patients from Other racial groups (p <.0001). The same post-hoc analysis was performed on patients with private insurance. Again, the results show no significant difference between White patients and patients of Other races (p <.392). However, significant differences were found between both White and Black patients (p <.0001) and between Black and patients from Other racial groups (p <.0001). Therefore, we can conclude that Black patients, regardless of insurance status, have significantly more hospital admissions through the emergency room than both White patients and patients of Other races. Based on the results discussed above, it is difficult to differentiate what factor contributes most to using the emergency room as a source of admission. A racial difference does exist, with Blacks using the emergency room more than Whites or Other racial groups as a source of admission to the hospital. However, a difference was also found for insurance status,

13 13 with those on government insurance or paying on their own entering the hospital through the emergency room at higher levels than those with private insurance. To find out which factor has a greater influence on source of admission, a logistic regression was performed, with the dichotomous variables, White (vs. non-white), Other (vs. non-other), and insurance status (govt./self-pay vs. private insurance) being regressed upon source of hospital admission through physician referral. Table 7 Logistic Regression Coefficients of Race and Insurance Type on Source of Hospital Admission Race** Race and Insurance*** Predictors Coefficient S.E. Exp(B) Coefficient S.E. Exp(B) White.578* * Other.538* * Insurance (1=private insurance Type.776* Constant -.804* * *p <.0001, ** R2 =.012, *** R2 =.045 The model above shows highly significant coefficients, producing results that show both racial differences and insurance status differences for source of hospital admission. Specifically, White patients are significantly different from Blacks in terms of source of hospital admission. The directionality of the coefficient shows that White patients have significantly greater odds of being admitted to the hospital through referral than through the emergency room (B =.578, p <.0001). The same relationship was found for patients of Other races in comparison to Black patients (B =.538, p <.0001). However, this model was extremely weak in predicting Source of Admission to the hospital, R 2 =.012. The variable Insurance status was added to the model, and a statistically significant relationship was found (B =.776, p <.0001),

14 14 indicating that patients with private insurance have significantly greater odds of being admitted to the hospital through referral than through the emergency room. Again, this model was not a strong predictor of Source of Admission, R 2 =.045. In an attempt to further understand the factors that affect Source of Admission, it was decided that more variables would be added to the model in an attempt to account for more than 4.5% of the variance in Source of Admission to the hospital. Added to the model were the demographic variables of Sex and Age and variables that assessed hospital characteristics. These included Hospital Type and Hospital Size. Tables 8-11 show the percent distributions for these new variables. Table 8 Percent Distribution of Sex Sex n % Male 40,078 39% Female 63,307 61% Total 104, % Table 9 Percent Distribution of Age Age Range n % , % , % , % , % , % , % , % , % Total 104, %

15 15 Table 10Percent Distribution of Hospital Type Hospital Type n % For Profit 6, % Government, non-federal 13, % Non-Profit, including religious 84, % Total 104, % Table 11 Frequencies, Hospital Size (total number of staffed beds) Number of Beds n % ,516 11% , % , % ,138 28% , % Total 104, % The variables assessed above: Sex, Age, Hospital Type, and Hospital Size were included in another logistic regression analysis, along with the original independent variables of Race and Insurance Type. Again, these variables were regressed upon the dependent variable of Source of Admission, physician referral. The results are shown in Table 12. All of the coefficients in the above analyses were significant. The model which included the additional variables accounted for a considerable amount of variance when compared to the previous models, R 2 =.099. The results show that White patients (B =.741, p <.0001) and patients of Other races (B =.479, p <.0001) have significantly greater odds of entering the hospital through referral as opposed to Black patients. We also see that patients on private insurance (B =.431, p <.0001) have significantly greater odds of entering the hospital through

16 16 referral than those on government assistance or self-payment. Patients who seek treatment at larger hospitals, 500+ beds (B =.346, p <.0001) and beds (B =.286, p <.0001) have significantly greater odds of entering the hospital through referral than patients who seek treatment at smaller hospitals. However, patients at medium sized hospitals, beds (B = -.103, p <.0001), have significantly lower odds of entering the hospital through referral than Table 12 Logistic Regression Coefficients of Race and Insurance Type and Other Potential Intervening Variables on Source of Hospital Admission Race 1 Race and Insurance 2 Race, Insurance, and other Variables 3 Predictors Coefficient S.E. Exp (B) Coefficient S.E. Exp (B) Coefficient S.E. Exp (B) White.578* * * Other.538* * * Insurance.776* * Type (private ins. = 1) Sex (female =.501* ) Hospital size * * * Hospital Type -.958* Government Non-Profit -.874* Age -.020* Constant * *p <.0001, 1R2 =.012, 2 R2 =.045, 3 R2 =.099 those who seek treatment at smaller hospitals. Also, patients who seek care at a Governmentowned hospital (B = -.958, p <.0001) and those patients who seek care at a Non-Profit hospital (B = -.874, p <.0001) have significantly lower odds of entering the hospital through referral than patients who seek care at a For Profit facility. Finally, younger patients (B = -.020, p <.0001) have significantly lower odds of entering the hospital through referral than older patients. As stated earlier, all of the coefficients were significant, which can be attributed in part to the

17 17 large sample size of 104,185 patients. Therefore, it is difficult to determine which variable, Race or Insurance Type, has a greater influence on Source of Admission to the hospital. To get at what effects are actually at play, a careful interpretation of the results is needed. Discussion As mentioned previously, the effects of sample size should not ignored in interpretation of the results. Although statistical significance is the measure of change or difference between to groups, means, outcomes, or measures, practical significance is just as important. This sample is very large, and therefore all chi-square analyses and logistic regression coefficients have significance levels of p < Thus, practical significance becomes evident when looking at the R 2 results. The finding that nine independent variables can be entered into a logistic regression analyses and only account for 9.9% of the variance is surprising, considering the strong statistical significance of the coefficients. The hypothesis of this study: Racial differences in access to healthcare, as measured by source of hospital admission, will be mediated by differences in health insurance status could be answered simply by looking at a few of the analyses. Table Four shows the anticipated racial differences, as stated in the hypothesis, with Black patients having significantly higher emergency room hospital admission rates than Whites (69.1% vs. 55.8%, p <.0001). Table Five, then, supports the idea that those patients on government insurance or self-payment use the emergency room as a source of entry at a significantly higher level than those on private insurance (65.8% vs. 46.5%, p <.0001). Thus, having established both predictions stated in the hypothesis, multivariate analyses should confirm the prediction. Table Six, in which a chi-square analysis was performed on Race and Source of Admission, controlling for Insurance Type, there is a consistent significant association between Race and Source of Admission. Regardless of insurance status, racial differences exist for both patients on Government Insurance or Self-Pay and patients with Private Insurance. Black patients, as opposed to White patients or patients of

MASSACHUSETTS RESIDENTS CENTRAL MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012

MASSACHUSETTS RESIDENTS CENTRAL MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012 ACUTE CARE HOSPITAL UTILIZATION TRENDS I N MASSACHUSETTS FY2009-2012 MASSACHUSETTS RESIDENTS CENTRAL MA Introduction The Center for Health Information and Analysis (CHIA) is publishing these inpatient,

More information

There are 5 demographic data elements that include gender, date of birth, race, ethnicity status,

There are 5 demographic data elements that include gender, date of birth, race, ethnicity status, Demographic and Data s There are 5 demographic data elements that include gender, date of birth, race, ethnicity status, and postal code of the patient. These elements are intended to be collected once

More information

The Role of Insurance in Providing Access to Cardiac Care in Maryland. Samuel L. Brown, Ph.D. University of Baltimore College of Public Affairs

The Role of Insurance in Providing Access to Cardiac Care in Maryland. Samuel L. Brown, Ph.D. University of Baltimore College of Public Affairs The Role of Insurance in Providing Access to Cardiac Care in Maryland Samuel L. Brown, Ph.D. University of Baltimore College of Public Affairs Heart Disease Heart Disease is the leading cause of death

More information

Essential Hospitals VITAL DATA. Results of America s Essential Hospitals Annual Hospital Characteristics Survey, FY 2012

Essential Hospitals VITAL DATA. Results of America s Essential Hospitals Annual Hospital Characteristics Survey, FY 2012 Essential Hospitals VITAL DATA Results of America s Essential Hospitals Annual Hospital Characteristics Survey, FY 2012 Published: July 2014 1 ABOUT AMERICA S ESSENTIAL HOSPITALS METHODOLOGY America s

More information

Appendix 1. Sociodemographic Characteristics for the Top and Bottom 10 States in the 2009 State Scorecard on Health System Performance

Appendix 1. Sociodemographic Characteristics for the Top and Bottom 10 States in the 2009 State Scorecard on Health System Performance Appendix 1. Sociodemographic Characteristics for the Top and Bottom 10 States in the 2009 State Scorecard on Health System Performance Resident Population in Millions (a) Median Annual Household Income

More information

MASSACHUSETTS RESIDENTS NORTHEAST MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012

MASSACHUSETTS RESIDENTS NORTHEAST MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012 ACUTE CARE HOSPITAL UTILIZATION TRENDS I N MASSACHUSETTS FY2009-2012 MASSACHUSETTS RESIDENTS NORTHEAST MA Introduction The Center for Health Information and Analysis (CHIA) is publishing these inpatient,

More information

By: Latarsha Chisholm, MSW, Ph.D. Department of Health Management & Informatics University of Central Florida

By: Latarsha Chisholm, MSW, Ph.D. Department of Health Management & Informatics University of Central Florida By: Latarsha Chisholm, MSW, Ph.D. Department of Health Management & Informatics University of Central Florida Health Disparities Health disparities refers to population-specific differences in the presence

More information

Essential Hospitals VITAL DATA. Results of America s Essential Hospitals Annual Hospital Characteristics Report, FY 2013

Essential Hospitals VITAL DATA. Results of America s Essential Hospitals Annual Hospital Characteristics Report, FY 2013 Essential Hospitals VITAL DATA Results of America s Essential Hospitals Annual Hospital Characteristics Report, FY 2013 Published: March 2015 1 ABOUT AMERICA S ESSENTIAL HOSPITALS METHODOLOGY America s

More information

White Paper. Medicare Part D Improves the Economic Well-Being of Low Income Seniors

White Paper. Medicare Part D Improves the Economic Well-Being of Low Income Seniors White Paper Medicare Part D Improves the Economic Well-Being of Low Income Seniors Kathleen Foley, PhD Barbara H. Johnson, MA February 2012 Table of Contents Executive Summary....................... 1

More information

Health Status, Health Insurance, and Medical Services Utilization: 2010 Household Economic Studies

Health Status, Health Insurance, and Medical Services Utilization: 2010 Household Economic Studies Health Status, Health Insurance, and Medical Services Utilization: 2010 Household Economic Studies Current Population Reports By Brett O Hara and Kyle Caswell Issued July 2013 P70-133RV INTRODUCTION The

More information

Home Health Care Today: Higher Acuity Level of Patients Highly skilled Professionals Costeffective Uses of Technology Innovative Care Techniques

Home Health Care Today: Higher Acuity Level of Patients Highly skilled Professionals Costeffective Uses of Technology Innovative Care Techniques Comprehensive EHR Infrastructure Across the Health Care System The goal of the Administration and the Department of Health and Human Services to achieve an infrastructure for interoperable electronic health

More information

Louisiana Report 2013

Louisiana Report 2013 Louisiana Report 2013 Prepared by Louisiana State University s Public Policy Research Lab For the Department of Health and Hospitals State of Louisiana December 2015 Introduction The Behavioral Risk Factor

More information

Strategies for Reduction of Inappropriate Emergency Department Use in the Outpatient Setting

Strategies for Reduction of Inappropriate Emergency Department Use in the Outpatient Setting Strategies for Reduction of Inappropriate Emergency Department Use in the Outpatient Setting By Bryce Elizabeth Holland Physician Assistant Student, Expected Graduation August 2014, University of Utah

More information

Health Care Access to Vulnerable Populations

Health Care Access to Vulnerable Populations Health Care Access to Vulnerable Populations Closing the Gap: Reducing Racial and Ethnic Disparities in Florida Rosebud L. Foster, ED.D. Access to Health Care The timely use of personal health services

More information

The National Survey of Children s Health 2011-2012 The Child

The National Survey of Children s Health 2011-2012 The Child The National Survey of Children s 11-12 The Child The National Survey of Children s measures children s health status, their health care, and their activities in and outside of school. Taken together,

More information

Understanding Prescription Assistance Programs (PAPs)

Understanding Prescription Assistance Programs (PAPs) Understanding Prescription Assistance Programs (PAPs) The use of prescription medicines has become an increasingly important part of quality medical care. Two out of every three visits to the doctor end

More information

Near-Elderly Adults, Ages 55-64: Health Insurance Coverage, Cost, and Access

Near-Elderly Adults, Ages 55-64: Health Insurance Coverage, Cost, and Access Near-Elderly Adults, Ages 55-64: Health Insurance Coverage, Cost, and Access Estimates From the Medical Expenditure Panel Survey, Center for Financing, Access, and Cost Trends, Agency for Healthcare Research

More information

Prepared by: Michael R. Cousineau, Dr.PH Gregory D. Stevens. Ph.D. With assistance from Jessica Van Gurt. USC Division of Community Health

Prepared by: Michael R. Cousineau, Dr.PH Gregory D. Stevens. Ph.D. With assistance from Jessica Van Gurt. USC Division of Community Health Disparities in Health in the United States A conceptual framework for a multi-disciplinary approach to understanding health disparities and proposing policy solutions towards their elimination First Draft

More information

Disparities in Realized Access: Patterns of Health Services Utilization by Insurance Status among Children with Asthma in Puerto Rico

Disparities in Realized Access: Patterns of Health Services Utilization by Insurance Status among Children with Asthma in Puerto Rico Disparities in Realized Access: Patterns of Health Services Utilization by Insurance Status among Children with Asthma in Puerto Rico Ruth Ríos-Motta, PhD, José A. Capriles-Quirós, MD, MPH, MHSA, Mario

More information

Racial and Ethnic Disparities in Women s Health Coverage and Access To Care Findings from the 2001 Kaiser Women s Health Survey

Racial and Ethnic Disparities in Women s Health Coverage and Access To Care Findings from the 2001 Kaiser Women s Health Survey March 2004 Racial and Ethnic Disparities in Women s Health Coverage and Access To Care Findings from the 2001 Kaiser Women s Health Survey Attention to racial and ethnic differences in health status and

More information

University Hospital Community Health Needs Assessment FY 2014

University Hospital Community Health Needs Assessment FY 2014 FY 2014 Prepared by Kathy Opromollo Executive Director of Ambulatory Care Services Newark New Jersey is the State s largest city. In striving to identify and address Newark s most pressing health care

More information

MASSACHUSETTS RESIDENTS WESTERN MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012

MASSACHUSETTS RESIDENTS WESTERN MA. Acute Care Hospital Utilization Trends in Massachusetts FY2009-2012 ACUTE CARE HOSPITAL UTILIZATION TRENDS I N MASSACHUSETTS FY2009-2012 MASSACHUSETTS RESIDENTS WESTERN MA Introduction The Center for Health Information and Analysis (CHIA) is publishing these inpatient,

More information

Racial Disparities in US Healthcare

Racial Disparities in US Healthcare Racial Disparities in US Healthcare Paul H. Johnson, Jr. Ph.D. Candidate University of Wisconsin Madison School of Business Research partially funded by the National Institute of Mental Health: Ruth L.

More information

STATISTICAL BRIEF #87

STATISTICAL BRIEF #87 Agency for Healthcare Medical Expenditure Panel Survey Research and Quality STATISTICAL BRIEF #87 July 2005 Attitudes toward Health Insurance among Adults Age 18 and Over Steve Machlin and Kelly Carper

More information

Results from the Commonwealth Fund s State Scorecard on Health System Performance Kansas in comparison to Iowa

Results from the Commonwealth Fund s State Scorecard on Health System Performance Kansas in comparison to Iowa Results from the Commonwealth Fund s State Scorecard on Health System Performance Kansas in comparison to Iowa Aiming Higher: Results from a State Scorecard on Health System Performance, published by the

More information

WILL EQUITY BE ACHIEVED THROUGH HEALTH CARE REFORM? John Z. Ayanian, MD, MPP

WILL EQUITY BE ACHIEVED THROUGH HEALTH CARE REFORM? John Z. Ayanian, MD, MPP WILL EQUITY BE ACHIEVED THROUGH HEALTH CARE REFORM? John Z. Ayanian, MD, MPP Brigham and Women s Hospital Harvard Medical School Harvard School of Public Health BWH Patient-Centered Outcomes Seminar April

More information

Final Questionnaire. Survey on Disparities in Quality of Health Care: Spring 2001

Final Questionnaire. Survey on Disparities in Quality of Health Care: Spring 2001 Final Questionnaire Survey on Disparities in Quality of Health Care: Spring 2001 Prepared by Princeton Survey Research Associates for the Commonwealth Fund 9.19.01 N= 8,290 Adults over 18 Aprox 1,000 Hispanic

More information

Health Insurance by Race/Ethnicity: 2008

Health Insurance by Race/Ethnicity: 2008 2008 WASHINGTON STATE POPULATION SURVEY Research Brief No. 52 December 2008 U WASHINGTON STATE OFFICE OF FINANCIAL MANAGEMENT Health Insurance by Race/Ethnicity: 2008 Contributor: Erica Gardner sing data

More information

INSIGHT on the Issues

INSIGHT on the Issues INSIGHT on the Issues AARP Public Policy Institute Medicare Beneficiaries Out-of-Pocket for Health Care Claire Noel-Miller, PhD AARP Public Policy Institute Medicare beneficiaries spent a median of $3,138

More information

Nursing Supply and Demand Study Acute Care

Nursing Supply and Demand Study Acute Care 2014 Nursing Supply and Demand Study Acute Care Greater Cincinnati Health Council 2100 Sherman Avenue, Suite 100 Cincinnati, OH 45212-2775 Phone: (513) 531-0200 Table of Contents I. Introduction and Executive

More information

Health Concern Access to Care

Health Concern Access to Care 12 2012-2013 Guilford County Department of Public Health Community Health Assessment Health Concern Access to Care Access to quality clinical care, while not the largest contributing factor to individual

More information

Urgent Care. A Brief Overview of Urgent Care and Opportunities in an Era of Health Care Reform. Presented at NCSL, August 2014 A SNAPSHOT

Urgent Care. A Brief Overview of Urgent Care and Opportunities in an Era of Health Care Reform. Presented at NCSL, August 2014 A SNAPSHOT Urgent Care A Brief Overview of Urgent Care and Opportunities in an Era of Health Care Reform Presented at NCSL, August 2014 A SNAPSHOT 1 What Is Urgent Care? Health care provided on a walk in, no appointment

More information

The Value of OTC Medicine to the United States. January 2012

The Value of OTC Medicine to the United States. January 2012 The Value of OTC Medicine to the United States January 2012 Table of Contents 3 Executive Summary 5 Study Methodology 7 Study Findings 10 Sources 2 Executive Summary For millions of Americans, over-the-counter

More information

Frequently Asked Questions Regarding At Home and Inpatient Hospice Care

Frequently Asked Questions Regarding At Home and Inpatient Hospice Care Frequently Asked Questions Regarding At Home and Inpatient Hospice Care Contents Page: Topic Overview Assistance in Consideration Process Locations in Which VNA Provides Hospice Care Determination of Type

More information

A Family Caregiver s Guide to Urgent Care Centers

A Family Caregiver s Guide to Urgent Care Centers Family Caregiver Guide A Family Caregiver s Guide to Urgent Care Centers Urgent care centers help fill the gap between a doctor s office and a hospital s emergency room (ER). They provide treatment for

More information

Medicare Beneficiaries Out-of-Pocket Spending for Health Care

Medicare Beneficiaries Out-of-Pocket Spending for Health Care Insight on the Issues OCTOBER 2015 Beneficiaries Out-of-Pocket Spending for Health Care Claire Noel-Miller, MPA, PhD AARP Public Policy Institute Half of all beneficiaries in the fee-for-service program

More information

Estimated Population Responding on Item 25,196,036 2,288,572 3,030,297 5,415,134 4,945,979 5,256,419 4,116,133 Medicare 39.3 (0.2)

Estimated Population Responding on Item 25,196,036 2,288,572 3,030,297 5,415,134 4,945,979 5,256,419 4,116,133 Medicare 39.3 (0.2) Table 3-15. Percent Distribution of Veterans by Type of Health Insurance and Age 35 Years 35-44 Years 2001 National Survey of Veterans (NSV) - March, 2003 - Page 140 45-54 Years 55-64 Years 65-74 Years

More information

REGISTRATION FORM. How would you like to receive health information? Electronic Paper In Person. Daytime Phone Preferred.

REGISTRATION FORM. How would you like to receive health information? Electronic Paper In Person. Daytime Phone Preferred. Signature Preferred Pharmacy Referral Info Emergency Contact Guarantor Information Patient Information Name (Last, First, MI) REGISTRATION FORM Today's Date Street Address City State Zip Gender M F SSN

More information

Physician address. Physician phone

Physician address. Physician phone PATIENT QUESTIONNAIRE Name (first, middle initial, last) Address City, State, Zip Social security number Michigan SportsMedicine and Orthopedic Center www.michigansportsmedicine.com Your family physician

More information

Reducing Hospital Readmissions & The Affordable Care Act

Reducing Hospital Readmissions & The Affordable Care Act Reducing Hospital Readmissions & The Affordable Care Act The Game Has Changed Drastically Reducing MSPB Measures Chuck Bongiovanni, MSW, MBA, NCRP, CSA, CFE Chuck Bongiovanni, MSW, MBA, NCRP, CSA, CFE

More information

GAO HEALTH INSURANCE. Report to the Committee on Health, Education, Labor, and Pensions, U.S. Senate. United States Government Accountability Office

GAO HEALTH INSURANCE. Report to the Committee on Health, Education, Labor, and Pensions, U.S. Senate. United States Government Accountability Office GAO United States Government Accountability Office Report to the Committee on Health, Education, Labor, and Pensions, U.S. Senate March 2008 HEALTH INSURANCE Most College Students Are Covered through Employer-Sponsored

More information

Educational Attainment of Veterans: 2000 to 2009

Educational Attainment of Veterans: 2000 to 2009 Educational Attainment of Veterans: to 9 January 11 NCVAS National Center for Veterans Analysis and Statistics Data Source and Methods Data for this analysis come from years of the Current Population Survey

More information

Disparities in Access and Use of Skilled Nursing Services by Income and Racial-Ethnic Status in California

Disparities in Access and Use of Skilled Nursing Services by Income and Racial-Ethnic Status in California Disparities in Access and Use of Skilled Nursing Services by Income and Racial-Ethnic Status in California Vivian Y. Wu Background Concerns about Disparities in Long-Term Care Services The baby boomer

More information

STATISTICAL BRIEF #113

STATISTICAL BRIEF #113 Medical Expenditure Panel Survey STATISTICAL BRIEF #113 Agency for Healthcare Research and Quality January 26 Children s Dental Care: Periodicity of Checkups and Access to Care, 23 May Chu Introduction

More information

Running head: NATIONAL INSURANCE 1. National Health Insurance. Marijo Johnson. Ferris State University

Running head: NATIONAL INSURANCE 1. National Health Insurance. Marijo Johnson. Ferris State University Running head: NATIONAL INSURANCE 1 National Health Insurance Marijo Johnson Ferris State University NATIONAL INSURANCE 2 Abstract National insurance is a controversial alternative to health care coverage

More information

Medicare- Medicaid Enrollee State Profile

Medicare- Medicaid Enrollee State Profile Medicare- Medicaid Enrollee State Profile Montana Centers for Medicare & Medicaid Services Introduction... 1 At a Glance... 1 Eligibility... 2 Demographics... 3 Chronic Conditions... 4 Utilization... 6

More information

Kaiser Low-Income Coverage and Access Survey

Kaiser Low-Income Coverage and Access Survey Kaiser Low-Income Coverage and Access Survey Spotlight on Uninsured Parents: December 2007 How a Lack of Coverage Affects Parents and Their Families How Trends in the Health Care System Affect Low-Income

More information

PATIENT INFORMATION - Please complete and/or verify all information and make changes as necessary.

PATIENT INFORMATION - Please complete and/or verify all information and make changes as necessary. PATIENT INFORMATION - Please complete and/or verify all information and make changes as necessary. Today s : Are you here for an injury that is work-related? YES NO N/A Patient Name (First-Middle-Last)

More information

Physician and other health professional services

Physician and other health professional services O n l i n e A p p e n d i x e s 4 Physician and other health professional services 4-A O n l i n e A p p e n d i x Access to physician and other health professional services 4 a1 Access to physician care

More information

Electronic Health Records Intake Form

Electronic Health Records Intake Form Dr. Sam Yoder, D.C. 101 Winston Way Ste B Campbellsville, KY 42718 Electronic Health Records Intake Form In compliance with requirements for the government EHR incentive program First Name: Address: Last

More information

SUBJECT: CHARITY AND UNCOMPENSATED CARE 1 of 13 DEPARTMENT: BUSINESS OFFICE REVISED: 10/2012

SUBJECT: CHARITY AND UNCOMPENSATED CARE 1 of 13 DEPARTMENT: BUSINESS OFFICE REVISED: 10/2012 REFERENCE # SUBJECT: CHARITY AND UNCOMPENSATED CARE 1 of 13 DEPARTMENT: BUSINESS OFFICE REVISED: 10/2012 CHARITY AND UNCOMPENSATED CARE Purpose To provide definition of health care assistance to eligible

More information

DISPARITIES IN HEALTHCARE QUALITY AMONG RACIAL AND ETHNIC GROUPS

DISPARITIES IN HEALTHCARE QUALITY AMONG RACIAL AND ETHNIC GROUPS DISPARITIES IN HEALTHCARE QUALITY AMONG RACIAL AND ETHNIC GROUPS Selected Findings From the 2011 National Healthcare Quality and Disparities Reports Introduction Each year since 2003, the Agency for Healthcare

More information

New Patient Packet. Marital Status: Single Married Divorced Separated Widowed Patient SSN: Address:

New Patient Packet. Marital Status: Single Married Divorced Separated Widowed Patient SSN:  Address: Patient Information New Patient Packet Patient First Name: Middle Initial: Last Name: Address: City: State: ZIP: Home Phone: Cell Phone: Work Phone: May we leave a voicemail? yes no May we leave a voicemail?

More information

Application. For Veterans Care Health Insurance. Veterans Care covers veterans who need health insurance. Other Important Information

Application. For Veterans Care Health Insurance. Veterans Care covers veterans who need health insurance. Other Important Information Application For Veterans Care Health Insurance There are thousands of veterans in Illinois who are living without health insurance because they can t afford it. The citizens of Illinois feel a sense of

More information

FAMILY CONTACT INFORMATION

FAMILY CONTACT INFORMATION FAMILY CONTACT INFORMATION -------------------- PLEASE COMPLETE THIS FORM IN BLACK INK ONLY -------------------- Date Account # Children Names DOB Gender School Goes By Cell Phone # Email Address Please

More information

Racial and Ethnic Health Disparities in Health and Health Care Kansas City Regional Data

Racial and Ethnic Health Disparities in Health and Health Care Kansas City Regional Data Racial and Ethnic Health Disparities in Health and Health Care Kansas City Regional Data By Debbie Chase, MPA Consultant, Center for Health Policy University of Missouri -- Columbia 1 Quantitative Data

More information

CAHPS Clinician & Group Survey

CAHPS Clinician & Group Survey CAHPS Clinician & Group Survey Version: Adult Primary Care Questionnaire.0 Language: English Response Scale: points te regarding the -to- response scale: This questionnaire employs a fourpoint response

More information

An Analysis of the Health Insurance Coverage of Young Adults

An Analysis of the Health Insurance Coverage of Young Adults Gius, International Journal of Applied Economics, 7(1), March 2010, 1-17 1 An Analysis of the Health Insurance Coverage of Young Adults Mark P. Gius Quinnipiac University Abstract The purpose of the present

More information

Access to Health Services

Access to Health Services Ah Access to Health Services Access to Health Services HP 2020 Goal Improve access to comprehensive, quality health care services. HP 2020 Objectives Increase the proportion of persons with a usual primary

More information

Start Making the Most of Your Money!

Start Making the Most of Your Money! Start Making the Most of Your Money! Answer 23 simple questions and you will get a personal report with tips on money management and budgeting, staying healthy, and protecting your financial information.

More information

PATIENT INFORMATION INTAKE F O R M BESSMER CHIROPRACTIC P. C.

PATIENT INFORMATION INTAKE F O R M BESSMER CHIROPRACTIC P. C. PATIENT INFORMATION INTAKE F O R M BESSMER CHIROPRACTIC P. C. Date today: _ PERSONAL INFORMATION Full Name: SS#: Address: City: State: Home Phone: Cell Phone: W o r k Phone: Email: Birthdate: Age: Sex:

More information

Bryant T. Aldridge Rehabilitation Center Unit Specific Inclusive Diversity Analysis: CULTURAL COMPETENCY AND DIVERSITY PLAN February 2015

Bryant T. Aldridge Rehabilitation Center Unit Specific Inclusive Diversity Analysis: CULTURAL COMPETENCY AND DIVERSITY PLAN February 2015 Bryant T. Aldridge Rehabilitation Center Unit Specific Inclusive Diversity Analysis: CULTURAL COMPETENCY AND DIVERSITY PLAN February 2015 Prepared by Brian Agan A Cultural Competency and Inclusive Diversity

More information

Medicare- Medicaid Enrollee State Profile

Medicare- Medicaid Enrollee State Profile Medicare- Medicaid Enrollee State Profile North Centers for Medicare & Medicaid Services Introduction... 1 At a Glance... 1 Eligibility... 2 Demographics... 3 Chronic Conditions... 4 Utilization... 6 Spending...

More information

BOWLING GREEN INTERNAL MEDICINE AND PEDIATRICS ASSOCIATES TREATMENT AUTHORIZATIONS AND FINANCIAL POLICIES

BOWLING GREEN INTERNAL MEDICINE AND PEDIATRICS ASSOCIATES TREATMENT AUTHORIZATIONS AND FINANCIAL POLICIES BOWLING GREEN INTERNAL MEDICINE AND PEDIATRICS ASSOCIATES TREATMENT AUTHORIZATIONS AND FINANCIAL POLICIES Patient Name: Date: FINANCIAL POLICY FOR PATIENTS Effective July 10, 2000 our office has established

More information

Employment-Based Health Insurance: 2010

Employment-Based Health Insurance: 2010 Employment-Based Health Insurance: 2010 Household Economic Studies Hubert Janicki Issued February 2013 P70-134 INTRODUCTION More than half of the U.S. population (55.1 percent) had employment-based health

More information

Key Features of the Affordable Care Act, By Year

Key Features of the Affordable Care Act, By Year Page 1 of 10 Key Features of the Affordable Care Act, By Year On March 23, 2010, President Obama signed the Affordable Care Act. The law puts in place comprehensive health insurance reforms that will roll

More information

Application of Information Systems and Secondary Data. Lynda Burton, ScD Johns Hopkins University

Application of Information Systems and Secondary Data. Lynda Burton, ScD Johns Hopkins University This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this

More information

Health and Social Services Needs in Whitman County. 2015 Community Needs Assessment Results General Report COMMUNITY REPORT OF RESULTS

Health and Social Services Needs in Whitman County. 2015 Community Needs Assessment Results General Report COMMUNITY REPORT OF RESULTS COMMUNITY REPORT OF RESULTS This report contains an overview of the results collected by the Health and Social Services Needs in Whitman County Survey. A description of Whitman County, the survey process,

More information

In the absence of universal coverage and an effective primary care

In the absence of universal coverage and an effective primary care November 2000 Issue Brief Emergency Department Use in New York City: A Survey of Bronx Patients john billings, nina parikh, and tod mijanovich new york university The Commonwealth Fund is a private foundation

More information

Financial Assistance Policy for Healthcare Services

Financial Assistance Policy for Healthcare Services Policy Title: Financial Assistance Policy for Healthcare Services Policy ID: 179 Keywords patient financial assistance, charity care I. Purpose of Policy To establish a policy for the administration of

More information

The Health Insurance Marketplace in Iowa: The consumer perspective

The Health Insurance Marketplace in Iowa: The consumer perspective The Health Insurance in Iowa: The consumer perspective Final report to the Iowa Dept. of Public Health Peter Damiano* Suzanne Bentler* Daniel Shane* University of Iowa Public Policy Center* and College

More information

Healthcare Reform: Impact on Care for Low-Income and Uninsured Patients

Healthcare Reform: Impact on Care for Low-Income and Uninsured Patients Competency 4 Healthcare Reform: Impact on Care for Low-Income and Uninsured Patients Updated June 2014. Presented by: Lewis Foxhall, MD VP for Health Policy Professor, Clinical Cancer Prevention UT MD

More information

Will Expanding Medicaid Coverage to Low-Income Uninsured Childless Adults under the Affordable Care Act Improve Health? Evidence from Wisconsin

Will Expanding Medicaid Coverage to Low-Income Uninsured Childless Adults under the Affordable Care Act Improve Health? Evidence from Wisconsin Will Expanding Medicaid Coverage to Low-Income Uninsured Childless Adults under the Affordable Care Act Improve Health? Evidence from Wisconsin Thomas DeLeire, Ph.D., Laura Dague, M.A., Lindsey Leininger,

More information

FINDINGS FROM THE 2014 MASSACHUSETTS HEALTH INSURANCE SURVEY

FINDINGS FROM THE 2014 MASSACHUSETTS HEALTH INSURANCE SURVEY CENTER FOR HEALTH INFORMATION AND ANALYSIS FINDINGS FROM THE MASSACHUSETTS HEALTH INSURANCE SURVEY MAY 2015 Prepared by: Laura Skopec and Sharon K. Long, Urban Institute Susan Sherr, David Dutwin, and

More information

Racial and Ethnic Disparities in Health and Access to Care Among Older Adolescents

Racial and Ethnic Disparities in Health and Access to Care Among Older Adolescents NO.2 NO.2 JANUARY 2007 2 Racial and Ethnic Disparities in Health and Access to Care Among Older Adolescents By Harriette B. Fox, Margaret A. McManus, Matthew Zarit, Amy E. Cassedy, and Gerry Fairbrother

More information

STATISTICAL BRIEF #173

STATISTICAL BRIEF #173 Medical Expenditure Panel Survey STATISTICAL BRIEF #173 Agency for Healthcare Research and Quality June 27 Use of the Pap Test as a Cancer Screening Tool among Women Age 18 64, U.S. Noninstitutionalized

More information

EARLY VS. LATE ENROLLERS: DOES ENROLLMENT PROCRASTINATION AFFECT ACADEMIC SUCCESS? 2007-08

EARLY VS. LATE ENROLLERS: DOES ENROLLMENT PROCRASTINATION AFFECT ACADEMIC SUCCESS? 2007-08 EARLY VS. LATE ENROLLERS: DOES ENROLLMENT PROCRASTINATION AFFECT ACADEMIC SUCCESS? 2007-08 PURPOSE Matthew Wetstein, Alyssa Nguyen & Brianna Hays The purpose of the present study was to identify specific

More information

Timeline: Key Feature Implementations of the Affordable Care Act

Timeline: Key Feature Implementations of the Affordable Care Act Timeline: Key Feature Implementations of the Affordable Care Act The Affordable Care Act, signed on March 23, 2010, puts in place health insurance reforms that will roll out incrementally over the next

More information

Predicting Successful Completion of the Nursing Program: An Analysis of Prerequisites and Demographic Variables

Predicting Successful Completion of the Nursing Program: An Analysis of Prerequisites and Demographic Variables Predicting Successful Completion of the Nursing Program: An Analysis of Prerequisites and Demographic Variables Introduction In the summer of 2002, a research study commissioned by the Center for Student

More information

As the proportion of racial/

As the proportion of racial/ Treatment Episode Data Set The TEDS Report May 5, 1 Differences in Substance Abuse Treatment Admissions between Mexican-American s and s As the proportion of racial/ ethnic minority groups within the United

More information

PLEASE COMPLETE AND RETURN

PLEASE COMPLETE AND RETURN PLEASE COMPLETE AND RETURN Voluntary Care Network Application Name of Client (Last) (First) (Middle Initial) Street Address Telephone (home) City State Zip Telephone (alternate) Date of Birth US Citizen

More information

Rural Health Information Technology Cooperative. Clinician Survey on Quality Improvement, Best Practice Guidelines, and Information Technology

Rural Health Information Technology Cooperative. Clinician Survey on Quality Improvement, Best Practice Guidelines, and Information Technology Rural Health Information Technology Cooperative Clinician Survey on Quality Improvement, Best Practice Guidelines, and Information Technology Conducted for: The Rural Healthcare Quality Network Conducted

More information

Single Payer Systems: Equity in Access to Care

Single Payer Systems: Equity in Access to Care Single Payer Systems: Equity in Access to Care Lynn A. Blewett University of Minnesota, School of Public Health The True Workings of Single Payer Systems: Lessons or Warnings for U.S. Reform Journal of

More information

The Effect of a Carve-out Advanced Access Scheduling System on No-show Rates

The Effect of a Carve-out Advanced Access Scheduling System on No-show Rates Practice Management Vol. 41, No. 1 51 The Effect of a Carve-out Advanced Access Scheduling System on No-show Rates Kevin J. Bennett, PhD; Elizabeth G. Baxley, MD Background and Objectives: The relationship

More information

Updated as of 05/15/13-1 -

Updated as of 05/15/13-1 - Updated as of 05/15/13-1 - GENERAL OFFICE POLICIES Thank you for choosing the Quiroz Adult Medicine Clinic, PA (QAMC) as your health care provider. The following general office policies are provided to

More information

Impact of Massachusetts Health Care Reform on Racial, Ethnic and Socioeconomic Disparities in Cardiovascular Care

Impact of Massachusetts Health Care Reform on Racial, Ethnic and Socioeconomic Disparities in Cardiovascular Care Impact of Massachusetts Health Care Reform on Racial, Ethnic and Socioeconomic Disparities in Cardiovascular Care Michelle A. Albert MD MPH Treacy S. Silbaugh B.S, John Z. Ayanian MD MPP, Ann Lovett RN

More information

Jon S. Howell, LNHA President & CEO Georgia Health Care Association November 18, 2013

Jon S. Howell, LNHA President & CEO Georgia Health Care Association November 18, 2013 Jon S. Howell, LNHA President & CEO Georgia Health Care Association November 18, 2013 GEORGIA HEALTH CARE ASSOCIATION Represents 336 skilled nursing facilities 13 SOURCE agencies 15 assisted living communities

More information

Survey of Nursing Education Programs: 2005 2006 School Year

Survey of Nursing Education Programs: 2005 2006 School Year Survey of Nursing Education Programs: 2005 2006 School Year EXECUTIVE SUMMARY In the fall of 2006, the Michigan Center for Nursing conducted a survey of nursing education programs in Michigan to collect

More information

AK Household Insurance Survey

AK Household Insurance Survey AK Household Insurance Survey Survey Instrument 2006 Alaska Health Care Insurance and Access Survey General Introduction: Hello, my name is insert from the Alaska Department of Health and Social Services.

More information

Community and Provider Health Care Project. It is the way they treat you that is the key community survey respondent.

Community and Provider Health Care Project. It is the way they treat you that is the key community survey respondent. Community and Provider Health Care Project It is the way they treat you that is the key community survey respondent. Advocate for an environment of trust with physicians as allies in overall care of patients

More information

2003 National Survey of College Graduates Nonresponse Bias Analysis 1

2003 National Survey of College Graduates Nonresponse Bias Analysis 1 2003 National Survey of College Graduates Nonresponse Bias Analysis 1 Michael White U.S. Census Bureau, Washington, DC 20233 Abstract The National Survey of College Graduates (NSCG) is a longitudinal survey

More information

Appendix C: Online Health Care Poll

Appendix C: Online Health Care Poll Appendix C: Online Health Care Poll Internet Poll through May 14, 2006 (10,512 responses) 1. How much do you agree or disagree with the following statement about health insurance coverage and public policy

More information

Colorado Choice Health Plans

Colorado Choice Health Plans Quality Overview Colorado Choice Health Plans Accreditation Exchange Product Accrediting Organization: Accreditation Status: URAC Health Plan Accreditation (Marketplace HMO) Provisional Accreditation Commercial

More information

Dr. Ronnie Pollard, DPM 1563 Gilpin Street Denver, CO 80218 303-388-0976 www.elevationfoot.com

Dr. Ronnie Pollard, DPM 1563 Gilpin Street Denver, CO 80218 303-388-0976 www.elevationfoot.com 1 Dr. Ronnie Pollard, DPM 1563 Gilpin Street Denver, CO 80218 303-388-0976 www.elevationfoot.com DEMOGRAPHICS & INSURANCE Patient Information Name: (First) (MI) (Last) SS#: DOB: Sex: Male Female Address:

More information

Prepared By: Erica Crall & Lucien Wulsin, Jr.

Prepared By: Erica Crall & Lucien Wulsin, Jr. Insure the Uninsured Project San Diego County Counties, Clinics, Hospitals, Managed Care and the Uninsured: Ten-Year Trend Report (1996-2006) Prepared By: Erica Crall & Lucien Wulsin, Jr. COUNTY ECONOMY

More information

STATISTICAL BRIEF #8. Conditions Related to Uninsured Hospitalizations, 2003. Highlights. Introduction. Findings. May 2006

STATISTICAL BRIEF #8. Conditions Related to Uninsured Hospitalizations, 2003. Highlights. Introduction. Findings. May 2006 HEALTHCARE COST AND UTILIZATION PROJECT STATISTICAL BRIEF #8 Agency for Healthcare Research and Quality May 2006 Conditions Related to Uninsured Hospitalizations, 2003 Anne Elixhauser, Ph.D. and C. Allison

More information

Is Health Care Spending Higher under Medicaid or Private Insurance?

Is Health Care Spending Higher under Medicaid or Private Insurance? Jack Hadley John Holahan Is Health Care Spending Higher under Medicaid or Private Insurance? This paper addresses the question of whether Medicaid is in fact a high-cost program after adjusting for the

More information